nalgebra/tests/linalg/full_piv_lu.rs

use na::Matrix3;

#[test]
fn full_piv_lu_simple() {
    let m = Matrix3::new(
        2.0, -1.0,  0.0,
       -1.0,  2.0, -1.0,
        0.0, -1.0,  2.0);

    let lu = m.full_piv_lu();
    assert_eq!(lu.determinant(), 4.0);

    let (p, l, u, q) = lu.unpack();

    let mut lu = l * u;
    p.inv_permute_rows(&mut lu);
    q.inv_permute_columns(&mut lu);

    assert!(relative_eq!(m, lu, epsilon = 1.0e-7));
}

#[test]
fn full_piv_lu_simple_with_pivot() {
    let m = Matrix3::new(
        0.0, -1.0,  2.0,
       -1.0,  2.0, -1.0,
        2.0, -1.0,  0.0);

    let lu = m.full_piv_lu();
    assert_eq!(lu.determinant(), -4.0);

    let (p, l, u, q) = lu.unpack();

    let mut lu = l * u;
    p.inv_permute_rows(&mut lu);
    q.inv_permute_columns(&mut lu);

    assert!(relative_eq!(m, lu, epsilon = 1.0e-7));
}

#[cfg(feature = "arbitrary")]
mod quickcheck_tests {
    use std::cmp;
    use na::{DMatrix, Matrix4, Matrix4x3, Matrix5x3, Matrix3x5, DVector, Vector4};

    quickcheck! {
        fn full_piv_lu(m: DMatrix<f64>) -> bool {
            let mut m = m;
            if m.len() == 0 {
                m = DMatrix::new_random(1, 1);
            }

            let lu = m.clone().full_piv_lu();
            let (p, l, u, q) = lu.unpack();
            let mut lu = l * u;
            p.inv_permute_rows(&mut lu);
            q.inv_permute_columns(&mut lu);

            relative_eq!(m, lu, epsilon = 1.0e-7)
        }

        fn full_piv_lu_static_3_5(m: Matrix3x5<f64>) -> bool {
            let lu = m.full_piv_lu();
            let (p, l, u, q) = lu.unpack();
            let mut lu = l * u;
            p.inv_permute_rows(&mut lu);
            q.inv_permute_columns(&mut lu);

            relative_eq!(m, lu, epsilon = 1.0e-7)
        }

        fn full_piv_lu_static_5_3(m: Matrix5x3<f64>) -> bool {
            let lu = m.full_piv_lu();
            let (p, l, u, q) = lu.unpack();
            let mut lu = l * u;
            p.inv_permute_rows(&mut lu);
            q.inv_permute_columns(&mut lu);

            relative_eq!(m, lu, epsilon = 1.0e-7)
        }

        fn full_piv_lu_static_square(m: Matrix4<f64>) -> bool {
            let lu = m.full_piv_lu();
            let (p, l, u, q) = lu.unpack();
            let mut lu = l * u;
            p.inv_permute_rows(&mut lu);
            q.inv_permute_columns(&mut lu);

            relative_eq!(m, lu, epsilon = 1.0e-7)
        }

        fn full_piv_lu_solve(n: usize, nb: usize) -> bool {
            if n != 0 && nb != 0 {
                let n  = cmp::min(n, 50);  // To avoid slowing down the test too much.
                let nb = cmp::min(nb, 50); // To avoid slowing down the test too much.
                let m  = DMatrix::<f64>::new_random(n, n);

                let lu = m.clone().full_piv_lu();
                let b1 = DVector::new_random(n);
                let b2 = DMatrix::new_random(n, nb);

                let sol1 = lu.solve(&b1);
                let sol2 = lu.solve(&b2);

                return (sol1.is_none() || relative_eq!(&m * sol1.unwrap(), b1, epsilon = 1.0e-6)) &&
                       (sol2.is_none() || relative_eq!(&m * sol2.unwrap(), b2, epsilon = 1.0e-6))
            }

            return true;
        }

        fn full_piv_lu_solve_static(m: Matrix4<f64>) -> bool {
             let lu = m.full_piv_lu();
             let b1 = Vector4::new_random();
             let b2 = Matrix4x3::new_random();

             let sol1 = lu.solve(&b1);
             let sol2 = lu.solve(&b2);

             return (sol1.is_none() || relative_eq!(&m * sol1.unwrap(), b1, epsilon = 1.0e-6)) &&
                    (sol2.is_none() || relative_eq!(&m * sol2.unwrap(), b2, epsilon = 1.0e-6))
        }

        fn full_piv_lu_inverse(n: usize) -> bool {
            let n = cmp::max(1, cmp::min(n, 15)); // To avoid slowing down the test too much.
            let m = DMatrix::<f64>::new_random(n, n);

            let mut l = m.lower_triangle();
            let mut u = m.upper_triangle();

            // Ensure the matrix is well conditioned for inversion.
            l.fill_diagonal(1.0);
            u.fill_diagonal(1.0);
            let m = l * u;

            let m1  = m.clone().full_piv_lu().try_inverse().unwrap();
            let id1 = &m  * &m1;
            let id2 = &m1 * &m;

            return id1.is_identity(1.0e-5) && id2.is_identity(1.0e-5);
        }

        fn full_piv_lu_inverse_static(m: Matrix4<f64>) -> bool {
            let lu = m.full_piv_lu();

            if let Some(m1)  = lu.try_inverse() {
                let id1 = &m  * &m1;
                let id2 = &m1 * &m;

                id1.is_identity(1.0e-5) && id2.is_identity(1.0e-5)
            }
            else {
                true
            }
        }
    }
}